detection of obscured targetspeople.ee.duke.edu/~lcarin/scott1.pdf · 2003. 1. 28. · – the...

Detection of Obscured Targets

Waymond R. Scott, Jr. and James McclellanSchool of Electrical and Computer Engineering

Georgia Institute of TechnologyAtlanta, GA 30332-0250

waymond.scott@ece.gatech.edu404-894-3048

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 2

Outline

• Objectives• Sensor Systems

– Buried Structures– Buried Landmines

• Material Parameter Measurements• Near and Far Term Goals

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 3

Objectives for the Georgia Tech Effort on the Obscured Targets MURI

The objective of this research is to use a combination of theoretical simulation, experimental measurements, and signal processing to develop and understand innovative techniques for detecting obscured targets such as buried landmines and buried structures.

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 4

The Components of the Research are all Interrelated

Sensor System:Mine Detector,Buried StructureDetector, etc.

Probing Signals:Electromagnetic,Seismic, HybridPassive/Active.

Models: Theoretical,Large scale Numerical and Experimental

Underlying Physics:Wave Interactions,Material Properties,etc.

Signal Processing:Detection, Inversion, etc.

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 5

Outline

• Objectives• Sensor Systems

– Buried Structures– Buried Landmines

• Material Parameter Measurements• Near and Far Term Goals

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 6

Sensor Systems

• Buried Structure Detection– Is it feasible to use either active or passive seismic

techniques and/or electromagnetic techniques to detect buried structures?

– Many of the issues are similar to those for mine detection.

• Soil properties• Seismic/Electromagnetic wave interactions• Configuration• Signal processing• Ambient/target noise.

– Numerical and experimental models are also similar

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 7

Sensor Systems• Possible configurations for a sensor to detect buried structures.

– These can be independent or interdependent sensors.

Buried Structure

NoiseSource

AirSoil

Seismic wavesRadiated from Structure

Sensors to detect waves radiated from structure

Passive Seismic Active EM to Sense Vibrations

Buried Structure

NoiseSource

Air

Structure Vibrating due to Noise

Soil

VibrationSensing Radar

Electromagnetic Waves

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 8

Buried Structure: 2m X 3m X 3m room with 14cm thick concrete walls :

Internal Source

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 9

Buried Structure: 2m X 3m X 3m room with 14cm thick concrete walls :

External Source

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 10

Models• Large scale numerical and experimental models

will be developed for these systems.– Extensions of the models developed under Demining

MURI and ONR projects.– Used to develop an understanding of the underlying

physics.• Wave interactions• Material parameters

– Used to generate synthetics and test ideas• Robust signal processing algorithms• Physical theories• Measurement Configurations

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 11

Outline

• Objectives• Sensor Systems

– Buried Structures– Buried Landmines

• Material Parameter Measurements• Near and Far Term Goals

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 12

Sensor Systems• Mine Detection

– Extension of Seismic/Electromagnetic Sensor developed as part ofthe Demining MURI and ONR projects

– Improve signal processing• In situ characterization of the subsurface velocity profile• Better mine detection algorithms

– Improve agreement between and experimental and numerical models

• Better understand/measure elastic properties of the soil• Better understand/measure seismic wave interactions with mine

– How is the best way to configure such a system?– How is the best way to sense the seismic vibrations?– Can ambient seismic noise be used to detect mines?

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 13

Possible Configurations

S SN

Mine

Rayleigh Wave

Elastic Wave Source

Displacements

AirSoil

Sensor

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Support FrameSeismic Source

Elastic Wave

Sensor

Possible Configurations

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Photograph of the Experimental Model

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Photograph of the Uncovered Mines and Rocks.

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Single AT Mine Surrounded by Multiple AP Mines30 dB Scale

Experimental Model Numerical Model

The differences between these results are due to the inaccurate values of the material parameters used in the model.

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 18

Speed?• One of the most significant issues that must be overcome

to make a practical seismic mine detection system is measurement speed.

• We have been using a 4 second measurement time to maximize the signal to noise ratio in our laboratory measurements. – This is overkill for a practical system

• Lower signal to noise ratios are adequate to find mines.• A mine field will probably be much less noisy than our lab.• Real soils will be more linear than the sand in the laboratory.

• What are reasonable measurement times?– Data from an experiment at a US Government test facility– Synthesize the effects of shorter measurement times.

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 19

US Government Test Facility

• VS2.2 AT mine 1 inch deep– 24 cm Diameter by

11.5 cm Height– Plastic

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Surface Displacement over MineVersus Measurement Time

4s

1s

1/4 s

1/16 s

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Images: VS2.2 AT Mine: 1 inch deep30 dB Scale: Versus Measurement Time

4s

1/4s

1s

1/16s

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Possible Handheld Configuration

• Stationary seismic source• Hand scanned sensor• Audible presentation of

seismic waves

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Audible Presentation• The above images will be difficult to generate

with a hand held mine detector.• An audible presentation of the signals are easy to

generate and require essentially no signal processing.– The signal sensed by the radar is directly played to the

operator. – The incident signal can be clearly heard by the operator.

This gives him confidence that the incident signal is present.

– The mine signal sounds hollow and is clearly distinguishable from the incident signal

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 24

5 10 15 20 25

-60

-40

-20

0

20

40

60

disp

lace

men

t, y=

0

time (ms)

TS-50 Mine, 3.0 cm Deep, SandboxVisual Presentation; Waterfall Graph Audible Presentation;

Sound File

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 25

Outline

• Objectives• Sensor Systems

– Buried Structures– Buried Landmines

• Material Parameter Measurements• Near and Far Term Goals

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 26

Material Parameters

• Soil has very inhomogeneous and complex mechanical and electromagnetic properties

• These inhomogeneities and complexities are generally the limiting factor for subsurface sensing systems

• Techniques for measuring these properties in situ will be investigated – In situ measurements are necessary because disturbing

the soil significantly changes its material properties

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 27

Material Parameters• Spectral Analysis of Surface Wave (SASW) techniques are

used by geophysicist and civil engineers to make in situ measurements of the mechanical properties.– However, they are generally interested in much deeper structures.– We have found that the complexities of the near surface cause

problems for these techniques.• Modifications to existing SASW techniques and new

techniques will be investigated.– How should the measurement

system be set up?– How to calculate wave velocities?– How should the data be inverted?– Raleigh or Love waves?

MURI Kickoff/Progress 1-24-03 Scott and Mcclellan, Georgia Tech 28

Typical Surface Sensor ArraysUsed in Experimental Model and

at Field Test Sites

Linear Array of 16 Triaxial Accelerometers

Linear Array of